AI agents invoke app_focus to trigger actions in ScreenHand. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool triggers an external UI operation — changing window focus — which is an active system interaction rather than a passive read. It causes a side effect (foreground state change) but does not modify data, delete anything, or move money. Execute is the most appropriate category. Severity is low since misuse has minimal blast radius.
From the tool's definition Bring a running application to the foreground
Documented attack patterns abuse exactly the kind of access app_focus gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and ScreenHand, and nothing reaches the server without passing your rules. This is the rule we recommend for app_focus:
{
"version": "1",
"default": "deny",
"tools": {
"app_focus": {
"limits": [
{
"counter": "app_focus_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}app_focus stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Bring a running application to the foreground. It is categorised as a Execute tool in the ScreenHand MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ScreenHand MCP server in PolicyLayer and add a rule for app_focus: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches ScreenHand. Nothing to install.
app_focus is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the app_focus rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for app_focus. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
app_focus is provided by the ScreenHand MCP server (manushi4/screenhand). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from ScreenHand, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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89 ScreenHand tools catalogued and risk-classified — across an index of 43,000+ MCP servers.